DBMS > Blueflood vs. EDB Postgres vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison Blueflood vs. EDB Postgres vs. IBM Db2 warehouse vs. SAP SQL Anywhere vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Cloud-based data warehousing service

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.09
Rank	#353	Overall
	#33	Time Series DBMS

Score	2.18
Rank	#122	Overall
	#59	Relational DBMS

Score	1.34
Rank	#166	Overall
	#76	Relational DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

blueflood.io

www.enterprisedb.com

www.ibm.com/products/db2/warehouse

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

Technical documentation

github.com/rax-maas/blueflood/wiki

www.enterprisedb.com/docs

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

Rackspace

EnterpriseDB

IBM

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

2013

2005

2014

1992

2000

Current release

14, December 2021

17, July 2015

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

BSD for PostgreSQL-components

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
OS X

Linux
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

predefined scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML-type available, but no XML query functionality.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP REST

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
JDBC
ODBC
OLE DB

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

PL/SQL, SQL PL

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

by hash, list or range

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

yes

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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